Relationship between road traffic features and accidents: An application of two-stage decision-making approach for transportation engineers

Abstract

Introduction: An efficient decision-making process is one of the major necessities in the performance analysis of road safety for human safety and budget allocation procedure. Method: During the road safety analysis procedure, data envelopment analysis (DEA) supports policymakers in differentiating between risky and safe segments of a homogeneous highway. Cross risk, an extension of the DEA models, provides more information about risky segments for ranking purpose. After the identification of risky segments, the next goal is to identify those factors that are major contributors in making the segments risky. Results: This research proposes a methodology to analyze road safety performance by using a combination of DEA with the decision tree (DT) technique. The proposed methodology not only provides a facility to identify problematic road segments with the help of DEA but also identifies contributing factors with the help of DT. Practical applications: The application of the proposed model will help the policymakers to identify the major factors contributing to road accidents and to analyze the safety performance of road infrastructure to help allocate the budget during the decision-making process.